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Offline RL

726 papers

Papers per year

2
60
37
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'25

Papers

MOPO: Model-based Offline Policy Optimization NIPS 2020
Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis NIPS 2020
BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning NIPS 2020
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding NIPS 2020
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation NIPS 2020
MOReL: Model-Based Offline Reinforcement Learning NIPS 2020
Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement Learning NIPS 2020
Learning Dexterous Manipulation from Suboptimal Experts CORL 2020
PLAS: Latent Action Space for Offline Reinforcement Learning CORL 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning CORL 2020
BAR — A Reinforcement Learning Agent for Bounding-Box Automated Refinement AAAI 2020
Attentive Experience Replay AAAI 2020
Off-Policy Evaluation in Partially Observable Environments AAAI 2020
Adaptive Trade-Offs in Off-Policy Learning AISTATS 2020
Conditional Importance Sampling for Off-Policy Learning AISTATS 2020
A Nonparametric Off-Policy Policy Gradient AISTATS 2020
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning AISTATS 2020
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning AISTATS 2020
Human-centric dialog training via offline reinforcement learning EMNLP 2020
An Optimistic Perspective on Offline Reinforcement Learning ICML 2020
Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation ICML 2020
Revisiting Fundamentals of Experience Replay ICML 2020
Accountable Off-Policy Evaluation With Kernel Bellman Statistics ICML 2020
Representations for Stable Off-Policy Reinforcement Learning ICML 2020
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions ICML 2020